class_docstr: Re-implementation of SE block -- squeezing spatially
  and exciting channel-wise described in::
  
      Roy et al., Concurrent Spatial and Channel Squeeze & Excitation
      in Fully Convolutional Networks, arXiv:1803.02579
class_docstr_tok: ["Re-implementation","of","SE","block","--","squeezing","spatially","and","exciting","channel-wise","described","in",":",":","Roy","et","al.",",","Concurrent","Spatial","and","Channel","Squeeze","&","Excitation","in","Fully","Convolutional","Networks",",","arXiv:1803.02579"]
code: def __init__(self, name="spatial_squeeze_excitation"):
      super(SpatialSELayer, self).__init__(name=name)
  
file_path: NiftyNet/niftynet/layer/squeeze_excitation.py
imports: from __future__ import absolute_import, print_function
  import tensorflow
  from niftynet.layer.base_layer import Layer
  from niftynet.layer.fully_connected import FullyConnectedLayer
  from niftynet.layer.convolution import ConvolutionalLayer
  from niftynet.utilities.util_common import look_up_operations
label_desc: Use image node_id 1 to create a new SpatialSELayer object from inherited base classes: Layer with example: obj = SpatialSELayer(name)